We prove that partial type reconstruction for the pure polymorphic *-calculus is undecidable by a reduction from the second-order unification problem, extending a previous result by H.-J. Boehm. We show further that partial type reconstruction remains undecidable even in a very small predicative fragment of the polymorphic *-calculus, which implies undecidability of partial type reconstruction for * ML as introduced by Harper, Mitchell, and Moggi.

We propose a type system ML F that generalizes ML with first-class polymorphism as in System F. We perform partial type reconstruction. As in ML and in opposition to System F, each typable expression admits a principal type, which can be inferred. Furthermore, all expressions of ML are well-typed, with a possibly more general type than in ML, without any need for type annotation. Only arguments of functions that are used polymorphically must be annotated, which allows to type all expressions of System F as well.

We propose a type system MLF that generalizes ML with first-class polymorphism as in System F. We perform partial type reconstruction. As in ML and in opposition to System F, each typable expression admits a principal type, which can be inferred. Furthermore, all expressions of ML are well-typed, with a possibly more general type than in ML, without any need for type annotation. Only arguments of functions that are used polymorphically must be annotated, which allows to type all expressions of System F as well.

Abstract not found

The value of polymorphism in programming languages has been demonstrated by languages such as ML [19]. Recent e cient implementations of ML have shown that a language with implicit polymorphism can be practical [1]. The core of ML's type system is limited, however, by the fact that only instances of polymorphic functions may be passed as arguments to other functions, but

Recent years have seen a revival of interest in extending ML’s predicative type inference system with impredicative quantification in the style of System F, for which type inference is undecidable. This paper suggests a modest extension of ML with System F types: the heart of the idea is to extend the language of types with unary universal and existential quantifiers. The introduction and elimination of a quantified type is never inferred but indicated explicitly by the programmer by supplying the quantified type itself. Quantified types co-exist with ordinary ML schemes, which are in turn implicitly introduced and eliminated at let-bindings and use sites, respectively. The resulting language, QML, does not impose any restriction on instantiating quantified variables with quantified types; neither let- nor λ-bound variables ever require a type annotation, even if the variable’s inferred scheme or type involves quantified types. This proposal, albeit more verbose in terms of annotations than others, is simple to specify, implement, understand, and formalize.

Abstract interpretation and type and effect systems are two well-known frameworks for the static analysis of programs. While abstract interpretation uses the program control-flow to approximate its run-time behavior, type and effect systems are based on the program structural syntax. The fundamental result of this paper is to show how these a priori distinct approaches can be related to each other, shedding a new light on their relative expressiveness. A single example of static analysis, namely a straightforward program time complexity estimator for the simply typed lambda-calculus with recursion, is used throughout the paper to present the core ideas. We showhowan abstract interpretation and a type and effect system can be designed for this analysis and prove them equivalent, thus paving the way toabetter understanding of the relative merits of these two frameworks.

We present the first type reconstruction system which combines the implicit typing of ML with the full power of the explicitly typed second-order polymorphic lambda calculus. The system will accept ML-style programs, explicitly typed programs, and programs that use explicit types for all first-class polymorphic values. We accomplish this exibility by providing both generic and explicitly-quanti ed polymorphic types, as well as operators which convert between these two forms of polymorphism. This type reconstruction system is an integral part of the FX-89 programming language. We present atype reconstruction algorithm for the system. The type reconstruction algorithm is proven sound and complete with respect to the formal typing rules.

Interpretation is an implicit part of today’s programming; it has great power but is overused and has significant costs. For example, interpreters are typically significantly hard to understand and hard to reason about. The methodology of “Totally Functional Programming” (TFP) is a reasoned attempt to redress the problem of interpretation. It incorporates an awareness of the undesirability of interpretation with observations that definitions and a certain style of programming appear to offer alternatives to it. Application of TFP is expected to lead to a number of significant outcomes, theoretical as well as practical. Primary among these are novel programming languages to lessen or eliminate the use of interpretation in programming, leading to better-quality software. However, TFP contains a number of lacunae in its current formulation, which hinder development of these outcomes. Among others, formal semantics and type-systems for TFP languages are yet to be discovered, the means to reduce interpretation in programs is to be determined, and a detailed explication is needed of interpretation, definition, and the differences between the two. Most important of all however is the need to develop a complete understanding of the nature of interpretation. In this work, suitable type-systems for TFP languages are identified, and guidance given regarding the construction of appropriate formal semantics. Techniques, based around the ‘fold’ operator, are identified and developed for modifying programs so as to reduce the amount of interpretation they contain. Interpretation as a means of language-extension is also investigated. v Finally, the nature of interpretation is considered. Numerous hypotheses relating to it considered in detail. Combining the results of those analyses with discoveries from elsewhere in this work leads to the proposal that interpretation is not, in fact, symbol-based computation, but is in fact something more fundamental: computation that varies with input. We discuss in detail various implications of this characterisation, including its practical application. An often more-useful property, ‘inherent interpretiveness’, is also motivated and discussed in depth. Overall, our inquiries act to give conceptual and theoretical foundations for practical TFP.